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  <title>Description of filter_binomial_1D</title>
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<h1>filter_binomial_1D
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<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
<div class="box"><strong>1D binomial filter (approximation to Gaussian filter)</strong></div>

<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
<div class="box"><strong>function f = filter_binomial_1D( r, show ) </strong></div>

<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
<div class="fragment"><pre class="comment"> 1D binomial filter (approximation to Gaussian filter)

 Creates a binomial filter of size 2*r+1 x 1.  This can be used to approximate the
 Gaussian distribution with sigma=sqrt((2*r+1)/4). For large r, should give same output
 as:
   g = fspecial( 'Gaussian', [2*r+1,1],sqrt((2*r+1)/4) );
 Given sigma, use r ~= 2*sigma^2.

 Use F = f*f' to get the equivalent 2d filter. 

 INPUTS
   r       - mask will have length 2r+1 and var=(2*r+1)/4
   show    - [optional] figure to use for display (no display if == 0)

 OUTPUTS
   f       - 1D binomial filter

 EXAMPLE
   r = 10;
   fbinom = filter_binomial_1D( r, 1 );
   fgauss = filter_gauss_1D( r, sqrt((2*r+1)/4), 2 );

 DATESTAMP
   11-Oct-2005  7:00pm
   
 See also <a href="filter_gauss_1D.html" class="code" title="function f = filter_gauss_1D( r, sigma, show )">FILTER_GAUSS_1D</a></pre></div>

<!-- crossreference -->
<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
This function calls:
<ul style="list-style-image:url(../matlabicon.gif)">
<li><a href="filter_visualize_1D.html" class="code" title="function filter_visualize_1D( f )">filter_visualize_1D</a>	Used to help visualize the a 1D filter.</li></ul>
This function is called by:
<ul style="list-style-image:url(../matlabicon.gif)">
<li><a href="FB_reconstruct_2D.html" class="code" title="function I2 = FB_reconstruct_2D( I, FB )">FB_reconstruct_2D</a>	Use to see how much image information is preserved in filter outputs.</li></ul>
<!-- crossreference -->



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